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<p>This paper presents a novel control strategy for maximum power point tracking (MPPT) in a standalone photovoltaic system based on the Takagi-Sugeno (T-S) fuzzy modeling and control framework to improve the efficiency of the generation system under the influence of fluctuations in weather conditions and connected load, as well as uncertainties in converter parameters. The proposed approach reformulates the MPPT problem as a stabilization problem of an augmented system by introducing the integral of the system’s output as an additional state variable. The stabilization conditions are then derived in terms of linear matrix inequalities (LMI) using Lyapunov stability theory and <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\mathcal {H}_\infty \)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi mathvariant="script">H</mi> <mi>∞</mi> </msub> </math></EquationSource> </InlineEquation> performance criteria, ensuring optimal tracking of the maximum power point and robustness against parameter uncertainties, load variations, and environmental fluctuations. The performance of the proposed controller is verified by simulations in MATLAB/Simulink environment and under different scenarios. Comparison results with perturb and observe (P&amp;O) algorithm and fuzzy logic control (FLC) method showed significant improvements in robustness, convergence speed, and tracking accuracy.</p>

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T-S Fuzzy Model-Based \(\mathcal {H}_\infty \) Control for a Standalone PV System with Variable Load and Parametric Uncertainties

  • 期刊论文

  • 发表日期：

    2026年4月7日

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  • Noureddine Boubekri,
  • Amine Kennouche,
  • Ihab Abderraouf Boulham,
  • Amira Kahlessenane

摘要

This paper presents a novel control strategy for maximum power point tracking (MPPT) in a standalone photovoltaic system based on the Takagi-Sugeno (T-S) fuzzy modeling and control framework to improve the efficiency of the generation system under the influence of fluctuations in weather conditions and connected load, as well as uncertainties in converter parameters. The proposed approach reformulates the MPPT problem as a stabilization problem of an augmented system by introducing the integral of the system’s output as an additional state variable. The stabilization conditions are then derived in terms of linear matrix inequalities (LMI) using Lyapunov stability theory and \(\mathcal {H}_\infty \) H ∞ performance criteria, ensuring optimal tracking of the maximum power point and robustness against parameter uncertainties, load variations, and environmental fluctuations. The performance of the proposed controller is verified by simulations in MATLAB/Simulink environment and under different scenarios. Comparison results with perturb and observe (P&O) algorithm and fuzzy logic control (FLC) method showed significant improvements in robustness, convergence speed, and tracking accuracy.